13 research outputs found

    Urban morphology parameters from global digital elevation models: implications for aerodynamic roughness for wind-speed estimation

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    Urban morphology and aerodynamic roughness parameters are derived from three global digital elevation models (GDEM): Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mission (SRTM), and TanDEM-X. Initially, each is compared to benchmark elevation data in London (UK). A moving window extracts ground heights from the GDEMs, generating terrain models with root-mean-square accuracy of up to 3 m. Subtraction of extracted ground heights provides roughness-element heights only, allowing for calculation of morphology parameters. The parameters are calculated for eight directional sectors of 1 km grid-squares. Apparent merging of roughness elements in all GDEMs causes height-based parameter underestimation, whilst plan and frontal areas are over- and under-estimated, respectively. Combined, these lead to an underestimation of morphometrically-derived aerodynamic roughness parameters. Parameter errors are least for the TanDEM-X data. Further comparison in five cities (Auckland, Greater London, New York, Sao Paulo, Tokyo) provides basis for empirical corrections to TanDEM-X-derived geometric parameters. These reduce the error in parameters across the cities and for a separate location. Meteorological observations in central London give insight to wind-speed estimation accuracy using roughness parameters from the different elevation databases. The proposed corrections to TanDEM-X parameters lead to improved wind-speed estimates, which combined with the improved spatial representation of parameters across cities demonstrates their potential for use in future studies

    Assessing methods to extrapolate the vertical wind-speed profile from surface observations in a city centre during strong winds

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    Knowledge of the vertical wind-speed profile in cities is important for the construction and insurance industries, wind energy predictions, and simulations of pollutant and toxic gas release. Here, five methods to estimate the spatially- and temporally- averaged wind-speed profile are compared in London: the logarithmic wind law (LOG); the Deaves and Harris equilibrium (DHe) and non-equilibrium (DHv) models; an adaptation of the power law (PL) and the Gryning et al. (GR) profile. Using measurements at 2.5 times the average building height, a source area model is used to determine aerodynamic roughness parameters using two morphometric methods, which assume homogeneous and variable roughness-element heights, respectively. Hourly-averaged wind speeds are extrapolated to 200 m above the canopy during strong wind conditions, and compared to wind speeds observed with Doppler lidar. Wind speeds are consistently underestimated if roughness-element height variability is not considered during aerodynamic parameter determination. Considering height variability, the resulting estimations with the DHe and GR profiles are marginally more similar to observations than the DHv profile, which is more accurate than the LOG and PL methods. An exception is in directions with more homogeneous fetch and a gradual reduction in upwind roughness, where the LOG and PL profiles are more appropriate

    Aerodynamic roughness variation with vegetation: analysis in a suburban neighbourhood and a city park

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    Local aerodynamic roughness parameters (zero-plane displacement, zd, and aerodynamic roughness length, z0) are determined for an urban park and a suburban neighbourhood with a new morphometric parameterisation that includes vegetation. Inter-seasonal analysis at the urban park demonstrates zd determined with two anemometric methods is responsive to vegetation state and is 1 – 4 m greater during leaf-on periods. The seasonal change and directional variability in the magnitude of zd is reproduced by the morphometric methods, which also indicate z0 can be more than halved during leaf-on periods. In the suburban neighbourhood during leaf-on, the anemometric and morphometric methods have similar directional variability for both zd and z0. Wind speeds at approximately 3 times the average roughness-element height are estimated most accurately when using a morphometric method which considers roughness-element height variability. Inclusion of vegetation in the morphometric parameterisation improves wind speed estimation in all cases. Results indicate that the influence of both vegetation and roughness-element height variability are important for accurate determination of local aerodynamic parameters and the associated wind-speed estimation

    Evaluation of urban local-scale aerodynamic parameters: implications for the vertical profile of wind speed and for source areas

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    Nine methods to determine local-scale aerodynamic roughness length (z0) and zero-plane displacement (zd) are compared at three sites (within 60 m of each other) in London, UK. Methods include three anemometric (single-level high frequency observations), six morphometric (surface geometry) and one reference-based approach (look-up tables). A footprint model is used with the morphometric methods in an iterative procedure. The results are insensitive to the initial zd and z0 estimates. Across the three sites, zd varies between 5 – 45 m depending upon the method used. Morphometric methods that incorporate roughness-element height variability agree better with anemometric methods, indicating zd is consistently greater than the local mean building height. Depending upon method and wind direction, z0 varies between 0.1 and 5 m with morphometric z0 consistently being 2 – 3 m larger than the anemometric z0. No morphometric method consistently resembles the anemometric methods. Wind-speed profiles observed with Doppler lidar provide additional data with which to assess the methods. Locally determined roughness parameters are used to extrapolate wind-speed profiles to a height roughly 200 m above the canopy. Wind-speed profiles extrapolated based on morphometric methods that account for roughness-element height variability are most similar to observations. The extent of the modelled source area for measurements varies by up to a factor of three, depending upon the morphometric method used to determine zd and z0

    Surface treatment response of AISI 2205 and AISI 304L steels: SMAT and plasma-nitriding

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    Sem informaçãoThe surface behaviour of surface mechanical attrition treated (SMATed) and plasma-nitrided AISI 2205 and AISI 304L steels was investigated in the present study. The intersection of the mechanical twins formed the submicron-size rhombic blocks in the surface region of the SMATed AISI 304L steel. However, such microstructural feature was absent in the SMATed AISI 2205 steel. The improvement in the surface-hardness due to the SMAT was about 70-80% for AISI 2205, and more than 100% for AISI 304L steel. The nature of passive film formed on the AISI 2205 steel was different from the AISI 304L steel. Passive film formed on the SMATed AISI 304L steel was relatively more unstable than that of the AISI 2205 steel at an elevated electric-potential and in a plasma environment. The plasma-nitriding response was affected due to the different passivation behaviour of the SMATed, and non-SMATed steels.353205215Sem informaçãoSem informaçãoSem informaçãoThis work was partially supported by the SERB [grant number EMR/2017/001196]. Their support is kindly acknowledged

    Confirmation and Follow-Up of Neurocysticercosis by Real-Time PCR in Cerebrospinal Fluid Samples of Patients Living in France ▿

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    Neurocysticercosis diagnosis is based on a combination of clinical, epidemiological, radiological, and immunological findings. We describe a real-time PCR assay for the confirmation of neurocysticercosis diagnosis in cerebrospinal fluid. The assay, tested on samples from nine patients living in France and diagnosed with neurocysticercosis, had a detection rate of 83.3% and 100% specificity

    Post‐HCV cure self‐reported changes in physical activity, eating behaviours, and fatigue in people living with HIV (ANRS CO13 HEPAVIH)

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